Abstract: This talk describes an Object-Oriented extension to RuleML
as a modular combination of three sublanguages. (1) User-level roles
provide frame-like slot representations as unordered argument
collections in atoms and complex terms. (2) URI-grounded clauses allow
for `webizing' using URIs as object identifiers for facts and rules.
(3) Order-sorted terms permit typed variables via Web links into
taxonomies such as RDF Schema class hierarchies, thus reusing the
Semantic Web's light-weight ontologies. Besides introducing the first
sublanguage with the Positional-Roled (ASCII) syntax, all three
sublanguages are introduced with the OO RuleML (XML) syntax. Their
semantics are sketched and their implementation paths are discussed.

Combining an inference engine with databases: a
rule server

Abstract: Complex Semantic Web applications require easy-to-use
tools for data and rule storage along with query mechanisms. We
describe a prototype server software RLS which is used similarly to the
ordinary usage of SQL RDBMS software in application programming. The
server combines first-order theorem provers with several query and rule
language layers for application development in the Semantic Web context.

Abstract. Due to a widely use of XML language in various application
domains, a well-established mechanism for the definition and
enforcement of security controls on specific accesses to XML documents
is demanded, in order to ensure that only authorized entities can
perform certain actions on the protected data. The proposed rule-based,
declarative approach supports definition of (possibly implicit and
complex) authorization rules on particular nodes within a document as
well as enforcement of multiple user-defined policies, specifying
selected mechanisms to resolve conflicts or to apply default
authorization. Moreover, by founded on both RDF and XDD theory, the
developed approach yields a simple yet flexible and interchangeable XML
access control model with well-defined declarative semantics.

Inference of Reactive Rules from Dependency
Models

Abstract. Reactive rules are rules that specify reactions to events.
In some cases it is easier and more intuitive for users to define a
dependency model rep-resenting an ontology. In this paper, we introduce
the ADI model and its infer-ence capabilities to run-time rule
execution. We introduce a case study on eT-rade and define the model
building blocks exemplified by this case study. Then we show the
specific rule language that is being used as the execution
infra-structure. We explain the inference mechanism and its dynamic
nature. The pa-per concludes with related work and a discussion about
its utilization.

Value-added Metatagging: Ontology and Rule based
Methods for Smarter Metadata

Abstract. In this paper we describe an ontology and rule based
system that significantly increases the productivity of those who
create metadata, and the quality of the metadata they produce. The
system suggests values for metadata elements using a combination of
four methods: inheritance, aggregation, content based similarity and
ontology-based similarity. Instead of aiming for automated metadata
generation we have developed a mechanism for suggesting the most
relevant values for a particular metadata field. In addition to
generating metadata from standard sources such as object content and
user profiles, the system benefits from considering metadata record
assemblies, metadata repositories, explicit domain ontologies and
inference rules as prime sources for metadata generations. In this
paper we first introduce the basic features of metadata systems and
provide a typology of metadata records and metadata elements. Next we
analyze the source of suggested values for metadata elements and
discuss four methods of metadata generation. We discuss how the
operations on objects the metadata are describing affect suggested
metadata values and we present decision tables for the metadata
generation scheduling algorithm. Finally, we discuss the use of our
system in tools developed for creating e-learning material conformant
with the SCORM reference model and the IEEE LTSC LOM standard.

Abstract. Situation Awareness involves the comprehension of the
state of a col-lection of objects in an evolving environment. This not
only includes an under-standing of the objects’ characteristics but
also an awareness of the significant relations that hold among the
objects at any point in time. Systems for estab-lishing situation
awareness require a knowledge representation for these objects and
relations. Traditional ontologies, as defined with a language like
DAML/OWL, are commonly used for such purposes. Unfortunately, these
lan-guages are insufficient for describing the conditions under which
specific rela-tions might hold true, which requires the explicit
representation of implications, as is provided by RuleML. This paper
describes an approach to knowledge rep-resentation for situation
awareness employing RuleML-based domain theories constructed over OWL
ontologies, presented in the context of its implementa-tion in a
Situation Awareness Assistant under development by the authors.
Suggestions are also made for additions to the RuleML specification.

Abstract. Rule-based and object-oriented techniques are rapidly mak-
ing their way into the infrastructure for representing and reasoning
about semantic information on the Web. Combining these two paradigms
has been an important objective and F-logic is a widely adopted
formalism that achieves this goal. However, the original F-logic was
lacking the notion of instance methods | one of the most common
object-oriented modeling tools. Extending F-logic with instance methods
poses new, non- trivial problems. It requires a dierent kind of
nonmonotonic inheritance and impacts much of the semantics of the
logic. In this paper we incorpo- rate instance methods into F-logic and
develop a complete model theory as well as a computation framework for
the extended language.

Rules and Defeasible Reasoning on the Semantic
Web

Abstract. This paper discusses some issues related to the use of
rules for the Semantic Web. We argue that rule formalisms and
rule-based technologies have to offer a lot for the Semantic Web. In
particular, they allow a simple treatment of defeasible reasoning,
which is essential for being able to capture many forms of commonsense
policies and specifications.

Bruce Spencer and Sandy Liu
National Research Council of Canada and University of New Brunswick,
Canada
{Bruce.Spencer, Sandy.Liu}@nrc.gc.ca
http://iit-iti.nrc-cnrc.gc.ca/groups/il_e.trx

We introduce the inference queue as a mechanism for communicating
and transforming data in Web services choreography. The insert
operation provides definite clauses to the inference queue, and the
remove operation generates output that is sound, complete, fair, and
irredundant. Both operations are thread safe and responsive. The
inference queue can form part of a highly configurable data
transformation system. Rules can also monitor for events of interest
based on the occurrence of certain conditions. Our suggestion of system
wide monitoring of communication is complementary to existing Web
services proposals.

Abstract. Web pages provide valuable knowledge for human
comprehension in text, tables, and mathematical notations. However, the
extraction and mainte-nance of structured rules from the Web pages are
not easy tasks. To tackle these problems, we adopt the eXtensible Rule
Markup Language framework. The RIML (Rule Identification Markup
Language) and RSML (Rule Structure Markup Language) are two compliant
representations in XRML for this pur-pose. RIML identifies the implicit
rules in the Web pages possibly using multi-ple pages to make a rule or
rule group. RSML specifies the complete rule struc-ture to be processed
by software agents or expert systems. In this study, we cover the
natural text, tables, and implicit numeric functions in the texts. In
order to fulfill the research goal, we define the necessary tags for
the rule extraction and maintenance in XRML. Typical ones include tags
for rule grouping, tabular rules, numeric operators, and functions. The
rule acquisi-tion process consists of rule base design, rule
identification with RIML, and rule structuring with RSML. The
maintenance process for the revisions that may occur either in Web
pages and structured rules is also described. The ap-proach is
demonstrated with the shipping cost comparison on the electronic book
stores.

RuleML Annotation for Automatic Collection
Levels on METS Metadata

Chieko Nakabasami
Toyo University, Japan
chiekon@toyonet.toyo.ac.jp

Abstract. In this paper, we propose a rule annotation method using
RuleML in the Metadata Encoding and Transmission Standard, called METS.
By putting rules into METS, the collection levels of digital contents
can be set automatically, and their re-organization can be performed
easily. Applying RuleML to the rule description is one of the promising
methods for re-organizing digital contents dynamically without human
effort. RuleML descriptions are implemented by inserting them into the
behavior section of METS, which is prepared for defining behaviors of
digital contents. A set of rules embedded into the behavior section may
designate how collection levels for target digital contents are set.